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# Anisa Dhana’s lagout for COVID-19 Confirmed Cases in the US
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## # A tibble: 14 x 2
## Admin2 Confirmed
## <chr> <dbl>
## 1 barnstable 1757
## 2 berkshire 711
## 3 bristol 10018
## 4 dukes and nantucket 157
## 5 essex 19765
## 6 franklin 410
## 7 hampden 8199
## 8 hampshire 1226
## 9 middlesex 27340
## 10 norfolk 10247
## 11 plymouth 9671
## 12 suffolk 24281
## 13 unassigned 2516
## 14 worcester 14344
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##Exercise 1 Worldwide COVID-19 Cases in Different Color
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##Exercise 2 Anisa Dhana’s lagout for COVID-19 Confirmed Cases in the US
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## Exercise 3 Number of Confirmed Cases by US County
daily_report_9_26_20 <- read_csv(url("https://raw.githubusercontent.com/CSSEGISandData/COVID-19/master/csse_covid_19_data/csse_covid_19_daily_reports/09-26-2020.csv")) %>%
rename(Long = "Long_") %>%
unite(Key, Admin2, Province_State, sep = ".") %>%
group_by(Key) %>%
summarize(Confirmed = sum(Confirmed)) %>%
mutate(Key = tolower(Key))
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us <- map_data("state")
counties <- map_data("county") %>%
unite(Key, subregion, region, sep = ".", remove = FALSE)
state_join <- left_join(counties, daily_report_9_26_20, by = c("Key"))
ggplot(data = us, mapping = aes(x = long, y = lat, group = group)) +
coord_fixed(1.3) +
borders("state", colour = "black") +
geom_polygon(data = state_join, aes(fill = Confirmed)) +
scale_fill_gradientn(colors = brewer.pal(n = 5, name = "BuPu"),
breaks = c(1, 10, 100, 1000, 10000, 100000),
trans = "log10", na.value = "White") +
ggtitle("Number of Confirmed Cases by US County") +
theme_gray()
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#Exercise 4
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#Script made readable